To further elaborate on our encoder design described in Section REF , we discuss what makes a CNN model perform well on our benchmark using image-CNN-based architecture as an example.
We use 18-layer ResNet[1]} from image-CNNs, and we change its input channels from three to one, and remove the FC layer. Then the modified version, named ResNet-like, accepts batch input with a shape [(B)atch, 1, (F)requency, (T)ime frame], and outputs [B, 512], 512-d embeddings.
